A pytorch implementation of https://arxiv.org/abs/1704.03477
In order to draw other things than cats, you will find more drawing data here: https://github.com/googlecreativelab/quickdraw-dataset
epoch 1900:
epoch 2400:
epoch 3400
Default hyperparameters for training has been found here: https://github.com/tensorflow/magenta/blob/master/magenta/models/sketch_rnn/README.md
Mix3D: Out-of-Context Data Augmentation for 3D Scenes (3DV 2021) Alexey Nekrasov*, Jonas Schult*, Or Litany, Bastian Leibe, Francis Engelmann Mix3D is
COVINS -- A Framework for Collaborative Visual-Inertial SLAM and Multi-Agent 3D Mapping Version 1.0 COVINS is an accurate, scalable, and versatile vis
TorchX TorchX: A PyTorch Extension Library for More Efficient Deep Learning. @misc{torchx, author = {Ansheng You and Changxu Wang}, title = {T
Reverse_Engineering_GMs Official Pytorch implementation of paper "Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Gener
Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography ====== This repository contains
PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor
Brain Tokyo Workshop 🧠🗼 This repo contains research materials released by members of the Google Brain team in Tokyo. Past Projects Weight Agnostic
torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor
The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base
Chex Chex is a library of utilities for helping to write reliable JAX code. This includes utils to help: Instrument your code (e.g. assertions) Debug
IPATool-py Python version of IPATool! Installation pip3 install -r requirements.txt Usage Quickstart: download app with specific bundleId into DIR: p
Learning where to learn - Gradient sparsity in meta and continual learning In this paper, we investigate gradient sparsity found by MAML in various co
DI Orchestrator DI Orchestrator is designed to manage DI (Decision Intelligence) jobs using Kubernetes Custom Resource and Operator. Prerequisites A w
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin
NLU Dataset Diagnostics This repository contains data and scripts to reproduce the results from our paper: Aarne Talman, Marianna Apidianaki, Stergios
Label-Efficient Semantic Segmentation with Diffusion Models Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion
Motion Representations for Articulated Animation This repository contains the source code for the CVPR'2021 paper Motion Representations for Articulat
structural-probes Codebase for testing whether hidden states of neural networks encode discrete structures. Based on the paper A Structural Probe for
Benchmarking-Chinese-Text-Recognition This repository contains datasets and baselines for benchmarking Chinese text recognition. Please see the corres
Higher-Order Transformers Kim J, Oh S, Hong S, Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs, NeurIPS 2021. [arxiv] W
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